Professional Experience

  • Present 2020

    Senior Lecturer

    Department of Computer science & Engineering, University of Moratuwa,
    Sri Lanka

  • 2021 2020

    Research Fellow

    LIRNEasia,
    Sri Lanka

  • 2020 2014

    Graduate Research/Teaching Fellow

    University of Oregon, Department of Computer and Information Science,
    USA.

  • 2018 2018

    Givens Associate

    Argonne National Laboratory,
    USA.

  • 2020 2011

    Lecturer

    Department of Computer science & Engineering, University of Moratuwa,
    Sri Lanka

  • 2014 2013

    Researcher

    LIRNEasia,
    Sri Lanka

  • 2014 2013

    Visiting Lecturer

    Northshore College of Business and Technology,
    Sri Lanka

Education

  • Ph.D. 2020

    Ph.D. in Computer & Information Science

    University of Oregon, USA

  • MS 2016

    MS in Computer & Information Science

    University of Oregon, USA

  • BSc2011

    B.Sc Engineering (Hons)in Computer Science & Engineering

    University of Moratuwa, Sri Lanka

Featured Research

Shift-of-Perspective Identification Within Legal Cases


G. Ratnayaka, T. Rupasinghe, N. de Silva, V. Gamage, M. Warushavithana, and A. Perera

Proceedings of the 3rd Workshop on Automated Detection, Extraction and Analysis of Semantic Information in Legal Texts, 2019, pp. to appear,

Arguments, counter-arguments, facts, and evidence obtained via previous court case transcripts are of essential need for individuals handling legal scenarios. Therefore, the process of automatic information extraction from court case transcripts can be considered to be of significant importance. This study is focused on the identification of sentences in court case transcripts which convey different perspectives on the same topic or entity. We combined several approaches based on semantic analysis, open information extraction, and sentiment analysis to achieve our objective. Then our methodology was evaluated with the help of human judges. The outcomes of the evaluation demonstrate that our system is successful in detecting situations where two sentences deliver different opinions on the same topic or entity. The proposed methodology can be used to facilitate other information extraction tasks related to the legal domain such as the detection of counter arguments and identification of opponent parties in a court case.